Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	142,450
2	Rhode Island	141,545
3	South Dakota	139,387
4	Utah	124,962
5	Tennessee	122,919
6	Arizona	119,454
7	Iowa	116,608
8	Nebraska	114,505
9	Wisconsin	114,490
10	Oklahoma	113,802
11	South Carolina	113,607
12	New Jersey	113,490
13	Arkansas	111,864
14	Delaware	109,114
15	Indiana	108,973
16	Alabama	108,316
17	Kansas	107,432
18	Illinois	107,344
19	New York	106,523
20	Idaho	105,871
21	Florida	105,788
22	Mississippi	105,396
23	Minnesota	104,447
24	Nevada	103,494
25	Montana	102,968
26	Georgia	102,275
27	Wyoming	101,534
28	Massachusetts	101,250
29	Kentucky	101,234
30	Texas	100,614
31	Louisiana	99,567
32	Missouri	98,822
33	Michigan	96,533
34	Connecticut	96,358
35	New Mexico	95,334
36	California	95,163
37	North Carolina	94,517
38	Alaska	93,718
39	Ohio	92,763
40	Pennsylvania	92,145
41	Colorado	91,545
42	West Virginia	87,390
43	Virginia	78,142
44	Maryland	75,027
45	New Hampshire	71,192
46	District of Columbia	68,289
47	Washington	54,850
48	Puerto Rico	52,966
49	Maine	47,766
50	Oregon	45,483
51	Vermont	37,726
52	Hawaii	23,776

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Colorado	198
2	Minnesota	193
3	Maine	184
4	Michigan	184
5	West Virginia	174
6	Delaware	163
7	Florida	147
8	Oregon	140
9	Washington	139
10	Pennsylvania	133
11	Illinois	127
12	Indiana	126
13	Puerto Rico	122
14	New York	121
15	Rhode Island	116
16	New Hampshire	113
17	North Carolina	111
18	Alaska	107
19	Massachusetts	102
20	South Carolina	100
21	Arizona	92
22	New Mexico	90
23	Nevada	86
24	Utah	83
25	Wyoming	81
26	North Dakota	80
27	Ohio	79
28	Vermont	79
29	Louisiana	78
30	Connecticut	77
31	Maryland	75
32	Tennessee	71
33	Wisconsin	68
34	Georgia	64
35	Iowa	64
36	Virginia	64
37	Idaho	63
38	Kentucky	62
39	Montana	61
40	Texas	61
41	Missouri	60
42	Nebraska	59
43	Mississippi	57
44	Oklahoma	56
45	Alabama	52
46	Hawaii	50
47	Arkansas	45
48	New Jersey	42
49	Kansas	39
50	California	37
51	South Dakota	29
52	District of Columbia	27

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,905
2	New York	2,682
3	Massachusetts	2,567
4	Rhode Island	2,539
5	Mississippi	2,430
6	Arizona	2,391
7	Connecticut	2,287
8	Louisiana	2,245
9	South Dakota	2,239
10	Alabama	2,238
11	Pennsylvania	2,077
12	North Dakota	2,006
13	Indiana	1,993
14	New Mexico	1,959
15	Michigan	1,942
16	Illinois	1,940
17	Arkansas	1,909
18	Iowa	1,896
19	South Carolina	1,863
20	Georgia	1,858
21	Nevada	1,787
22	Tennessee	1,783
23	Texas	1,752
24	Kansas	1,736
25	Oklahoma	1,726
26	Delaware	1,685
27	Florida	1,666
28	Ohio	1,662
29	California	1,577
30	District of Columbia	1,572
31	West Virginia	1,522
32	Missouri	1,521
33	Kentucky	1,499
34	Montana	1,489
35	Maryland	1,465
36	Wisconsin	1,314
37	Minnesota	1,298
38	Virginia	1,277
39	Nebraska	1,227
40	Wyoming	1,226
41	North Carolina	1,221
42	Idaho	1,154
43	Colorado	1,127
44	New Hampshire	967
45	Puerto Rico	743
46	Washington	739
47	Utah	694
48	Oregon	604
49	Maine	591
50	Alaska	453
51	Vermont	399
52	Hawaii	342

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Michigan	5
2	Delaware	4
3	Florida	2
4	Kentucky	2
5	California	1
6	Connecticut	1
7	Illinois	1
8	Indiana	1
9	Maryland	1
10	Massachusetts	1
11	New Jersey	1
12	New Mexico	1
13	New York	1
14	Pennsylvania	1
15	Puerto Rico	1
16	South Carolina	1
17	Virginia	1
18	West Virginia	1
19	Wisconsin	1
20	Alabama	0
21	Alaska	0
22	Arizona	0
23	Arkansas	0
24	Colorado	0
25	District of Columbia	0
26	Georgia	0
27	Hawaii	0
28	Idaho	0
29	Iowa	0
30	Kansas	0
31	Louisiana	0
32	Maine	0
33	Minnesota	0
34	Mississippi	0
35	Missouri	0
36	Montana	0
37	Nevada	0
38	New Hampshire	0
39	North Carolina	0
40	North Dakota	0
41	Ohio	0
42	Oklahoma	0
43	Oregon	0
44	Rhode Island	0
45	South Dakota	0
46	Tennessee	0
47	Texas	0
48	Utah	0
49	Vermont	0
50	Washington	0
51	Wyoming	0
52	Nebraska	-1

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Chattahoochee	Georgia	367,287	1	99
Crowley	Colorado	361,162	2	99
Bent	Colorado	274,341	3	99
Dewey	South Dakota	249,830	4	99
Lincoln	Arkansas	245,777	5	99
Davidson	Tennessee	142,054	187	94
Richland	South Carolina	111,976	982	68
York	South Carolina	110,919	1024	67
Orange	California	85,273	2210	29
Pierce	Washington	56,698	2862	8

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Foard	Texas	8,658	1	99
Galax city	Virginia	8,193	2	99
Jerauld	South Dakota	7,948	3	99
Emporia city	Virginia	7,856	4	99
Hancock	Georgia	7,686	5	99
Orange	California	1,577	1821	42
York	South Carolina	1,352	2085	33
Davidson	Tennessee	1,351	2087	33
Richland	South Carolina	1,345	2094	33
Pierce	Washington	729	2743	12

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.